Intelligent fire-fighting map training system

Abstract

The invention discloses an intelligent fire-fighting map training system, and relates to the field of intelligent fire fighting. Comprising a management end used for managing system content and training content; the plurality of training terminals are used for fire-fighting map training operation; the working logic of the intelligent fire-fighting map training system comprises the following steps that after a management end logs in the system, training data in a networking type data server are added, deleted and modified, and the training logic is determined; the networking type data server generates a plurality of independent map packets according to training logic, map points are randomly selected in each map packet, each map point is marked, and map data and training logic content are built in the networking type data server. According to the invention, the virtual map system is established, and then map training is carried out in the form of point selection marking and name matching, so that firefighters can quickly position fire-fighting places after receiving commands, and the fire-fighting efficiency is improved.

Description

Technical Field

[0001] The present invention relates to a field, and in particular to an intelligent fire map training system. Background Art

[0002] At present, catastrophic accidents occur frequently at home and abroad. With the development of social economy, the diversity and professionalism of disaster scenes have been caused, which has increased the difficulty of fire brigade training. If the troops need to adapt to various highly professional disaster scenes, the traditional approach is to invest a lot of manpower and material resources to build and simulate various disaster environments. Due to the large cost investment in such a physical simulation environment, training exercises cannot be carried out frequently. The emergence of virtual reality technology provides a new mode of emergency drills, simulating the accident scene into a virtual scene, thereby saving a lot of costs. Various accident environments can be artificially created here, and trainees can be organized to make correct responses. At the same time, due to the low hardware investment and the reproducibility and modifiability of the software, emergency rescue training based on VR virtual reality has become the most concerned training equipment development direction in various developed countries this century.

[0003] After searching, the Chinese patent publication number CN106816057B discloses a virtual firefighting training system, a backpack virtual combat training system and a backpack virtual terminal control system. The backpack virtual combat training system runs on a cloud server, and the backpack virtual terminal control system runs on a backpack terminal. The backpack virtual combat training service system located on the cloud server includes a user management module, a training data module, a scene data module, a data management system, a virtual fire scene environment generation module, a fire scene fluid AI control module, a device interaction effect control module, a multi-person collaborative AI control module, a virtual training scene system and a scene management system. The backpack virtual terminal control system located on the backpack terminal device includes a cloud rendering data flow control module, a scene display module, an interactive control module, a binocular stereoscopic image retinal projection system, a position acquisition module and an action acquisition module.

[0004] The above patent has the following deficiencies: during firefighting training, the determination of the firefighting location by firefighters is a prerequisite for all firefighting actions, and the above patent cannot provide map training for firefighters.

[0005] To this end, the present invention proposes an intelligent fire map training system. Summary of the invention

[0006] The purpose of the present invention is to solve the shortcomings of the prior art and to propose an intelligent fire map training system.

[0007] In order to achieve the above object, the present invention adopts the following technical solutions:

[0008] An intelligent fire map training system, comprising:

[0009] A management terminal, used to manage system content and training content;

[0010] Multiple training terminals for fire map training operations;

[0011] The networked data server has built-in map data and training logic content, and connects the management end and the training end through a networking algorithm, and has built-in data processing modules and data storage modules.

[0012] Preferably: the working logic of the intelligent fire map training system includes the following steps:

[0013] S1: After logging into the system, the management end adds, deletes, and modifies the training data in the networked data server and determines the training logic;

[0014] S2: The networked data server generates multiple independent map packages according to the training logic, and randomly selects map points in each map package and marks each map point;

[0015] S3: The trainer logs into the system through the training terminal to conduct training.

[0016] Preferably: the step S3 includes the following steps:

[0017] S31: After logging into the system, a training interface is generated, and the trainer selects a training map according to the interface;

[0018] S32: After selection, the map is displayed on the training interface, and the trainer enters the location name of the marked point according to the marked point on the map.

[0019] In the step S32, the training personnel inputs using a selective input method or a full input method.

[0020] Preferably: in the step S32, the logic of the selective input is:

[0021] A1: The training interface generates blank boxes corresponding to map markers;

[0022] A2: Set a drop-down arrow for each blank box;

[0023] A3: After the trainer clicks the drop-down arrow, multiple options are displayed;

[0024] A4: After the trainer selects one of the options, the system automatically selects the result and fills it into the blank box.

[0025] Preferably: in the step S32, the logic of full input is:

[0026] B1: The training interface generates blank boxes corresponding to map markers;

[0027] B2: After the trainer clicks the blank box, he / she enters the marked address name in the blank box;

[0028] B3: The system uses a tolerance algorithm to verify the input name and the actual name of the map marker.

[0029] Preferably: in step B3, the logic of the tolerance algorithm is:

[0030] B31: Set the tolerance ratio k;

[0031] B32: Get the total number of bytes p input by the trainer and the number of bytes q of the correct answer;

[0032] B33: Then compare and the size of k, where |p∩q| is the number of bytes that are the same in p and q;

[0033] B331: If It is determined that the information input by the trainer matches, and the result is "correct";

[0034] B332: If It is determined that the information input by the trainer does not match and the result is "error".

[0035] Preferably: the networking method of the networked data server comprises the following steps:

[0036] C1: Classify trainers according to their training content and training skills;

[0037] C2: After the trainer logs into the system through his account, each training terminal is bound to the trainer;

[0038] C3: Classify the training terminals according to the classification results of the trainers to form multiple categories;

[0039] C4: Establish a communication encrypted LAN in each category, and then establish a decoding communication connection between the management terminal and each category.

[0040] Preferably: in the C4 step, the encryption method comprises the following steps:

[0041] C41: Divide each sub-data table into multiple different sub-blocks, and number each sub-block sequentially;

[0042] C42: Encrypt different sub-blocks using different mathematical functions;

[0043] C43: The encrypted sub-blocks are then communicated using different threads.

[0044] Preferably: the C42 step specifically comprises the following steps:

[0045] C421: Create a mapping function set f i a And the encryption function set f i b ;

[0046] C422: For the original data, firstly select the corresponding mapping function according to the sub-block number, and transform the data through mapping to obtain the result;

[0047] C423: Select the encryption function corresponding to the number in the encryption function according to the integer part of the result obtained;

[0048] C424: The result of the mapping function transformation is then transformed twice using an encryption function to obtain the ciphertext.

[0049] Preferably: in the step C421, the mapping function is:

[0050] where x min is the minimum value in the data, x max is the maximum value in the data;

[0051] Where e is the base of natural logarithms;

[0052] where x min is the minimum value in the data, x max is the maximum value in the data;

[0053] f a (x) = x p , where p<1;

[0054] in

[0055] Any combination of .

[0056] The beneficial effects of the present invention are:

[0057] 1. The present invention establishes a virtual map system and then performs map training in the form of point selection marking and name matching, so that firefighters can quickly locate the firefighting location after receiving the order, thereby improving the firefighting efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0058] Figure 1 This is an architecture diagram of an intelligent fire map training system proposed by the present invention;

[0059] Figure 2 This is a logic diagram of an intelligent fire map training system proposed by the present invention. DETAILED DESCRIPTION

[0060] The technical solution of the present invention is further described in detail below in conjunction with specific implementation methods.

[0061] In the description of the present invention, it should be noted that, unless otherwise clearly specified and limited, the terms "installed", "connected", "connected", and "set" should be understood in a broad sense, for example, they can be fixedly connected or set, or detachably connected or set, or integrally connected or set. For ordinary technicians in this field, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0062] Embodiment 1:

[0063] An intelligent fire map training system, comprising:

[0064] A management terminal, used to manage system content and training content;

[0065] Multiple training terminals for fire map training operations;

[0066] The networked data server has built-in map data and training logic content, and connects the management end and the training end through a networking algorithm, and has built-in data processing modules and data storage modules.

[0067] The working logic of the intelligent fire map training system includes the following steps:

[0068] S1: After logging into the system, the management end adds, deletes, and modifies the training data in the networked data server and determines the training logic;

[0069] S2: The networked data server generates multiple independent map packages according to the training logic, and randomly selects map points in each map package and marks each map point;

[0070] S3: The trainer logs into the system through the training terminal to conduct training.

[0071] Embodiment 2:

[0072] An intelligent fire map training system, comprising:

[0073] A management terminal, used to manage system content and training content;

[0074] Multiple training terminals for fire map training operations;

[0075] The networked data server has built-in map data and training logic content, and connects the management end and the training end through a networking algorithm, and has built-in data processing modules and data storage modules.

[0076] The working logic of the intelligent fire map training system includes the following steps:

[0077] S1: After logging into the system, the management end adds, deletes, and modifies the training data in the networked data server and determines the training logic;

[0078] S2: The networked data server generates multiple independent map packages according to the training logic, and randomly selects map points in each map package and marks each map point;

[0079] S3: The trainer logs into the system through the training terminal to conduct training.

[0080] The step S3 includes the following steps:

[0081] S31: After logging into the system, a training interface is generated, and the trainer selects a training map according to the interface;

[0082] S32: After selection, the map is displayed on the training interface, and the trainer enters the location name of the marked point according to the marked point on the map.

[0083] Embodiment 3:

[0084] An intelligent fire map training system, comprising:

[0085] A management terminal, used to manage system content and training content;

[0086] Multiple training terminals for fire map training operations;

[0087] The networked data server has built-in map data and training logic content, and connects the management end and the training end through a networking algorithm, and has built-in data processing modules and data storage modules.

[0088] The working logic of the intelligent fire map training system includes the following steps:

[0089] S1: After logging into the system, the management end adds, deletes, and modifies the training data in the networked data server and determines the training logic;

[0090] S2: The networked data server generates multiple independent map packages according to the training logic, and randomly selects map points in each map package and marks each map point;

[0091] S3: The trainer logs into the system through the training terminal to conduct training.

[0092] The step S3 includes the following steps:

[0093] S31: After logging into the system, a training interface is generated, and the trainer selects a training map according to the interface;

[0094] S32: After selection, the map is displayed on the training interface, and the trainer enters the location name of the marked point according to the marked point on the map.

[0095] In the step S32, the training personnel inputs using a selective input method.

[0096] In the step S32, the logic of the selective input is:

[0097] A1: The training interface generates blank boxes corresponding to map markers;

[0098] A2: Set a drop-down arrow for each blank box;

[0099] A3: After the trainer clicks the drop-down arrow, multiple options are displayed;

[0100] A4: After the trainer selects one of the options, the system automatically selects the result and fills it into the blank box.

[0101] Embodiment 4:

[0102] An intelligent fire map training system, comprising:

[0103] A management terminal, used to manage system content and training content;

[0104] Multiple training terminals for fire map training operations;

[0105] The networked data server has built-in map data and training logic content, and connects the management end and the training end through a networking algorithm, and has built-in data processing modules and data storage modules.

[0106] The working logic of the intelligent fire map training system includes the following steps:

[0107] S1: After logging into the system, the management end adds, deletes, and modifies the training data in the networked data server and determines the training logic;

[0108] S2: The networked data server generates multiple independent map packages according to the training logic, and randomly selects map points in each map package and marks each map point;

[0109] S3: The trainer logs into the system through the training terminal to conduct training.

[0110] The step S3 includes the following steps:

[0111] S31: After logging into the system, a training interface is generated, and the trainer selects a training map according to the interface;

[0112] S32: After selection, the map is displayed on the training interface, and the trainer enters the location name of the marked point according to the marked point on the map.

[0113] In the step S32, the training personnel inputs using a full input method.

[0114] In the step S32, the logic of full input is:

[0115] B1: The training interface generates blank boxes corresponding to map markers;

[0116] B2: After the trainer clicks the blank box, he / she enters the marked address name in the blank box;

[0117] B3: The system uses a tolerance algorithm to verify the input name and the actual name of the map marker.

[0118] Embodiment 5:

[0119] An intelligent fire map training system, comprising:

[0120] A management terminal, used to manage system content and training content;

[0121] Multiple training terminals for fire map training operations;

[0122] The networked data server has built-in map data and training logic content, and connects the management end and the training end through a networking algorithm, and has built-in data processing modules and data storage modules.

[0123] The working logic of the intelligent fire map training system includes the following steps:

[0124] S1: After logging into the system, the management end adds, deletes, and modifies the training data in the networked data server and determines the training logic;

[0125] S2: The networked data server generates multiple independent map packages according to the training logic, and randomly selects map points in each map package and marks each map point;

[0126] S3: The trainer logs into the system through the training terminal to conduct training.

[0127] The step S3 includes the following steps:

[0128] S31: After logging into the system, a training interface is generated, and the trainer selects a training map according to the interface;

[0129] S32: After selection, the map is displayed on the training interface, and the trainer enters the location name of the marked point according to the marked point on the map.

[0130] In the step S32, the training personnel inputs using a full input method.

[0131] In the step S32, the logic of full input is:

[0132] B1: The training interface generates blank boxes corresponding to map markers;

[0133] B2: After the trainer clicks the blank box, he / she enters the marked address name in the blank box;

[0134] B3: The system uses a tolerance algorithm to verify the input name and the actual name of the map marker.

[0135] In step B3, the logic of the tolerance algorithm is:

[0136] B31: Set the tolerance ratio k;

[0137] B32: Get the total number of bytes p input by the trainer and the number of bytes q of the correct answer;

[0138] B33: Then compare and the size of k, where |p∩q| is the number of bytes that are the same in p and q;

[0139] B331: If It is determined that the information input by the trainer matches, and the result is "correct";

[0140] B332: If It is determined that the information input by the trainer does not match and the result is "error".

[0141] Embodiment 6:

[0142] An intelligent fire map training system, comprising:

[0143] A management terminal, used to manage system content and training content;

[0144] Multiple training terminals for fire map training operations;

[0145] The networked data server has built-in map data and training logic content, and connects the management end and the training end through a networking algorithm, and has built-in data processing modules and data storage modules.

[0146] The working logic of the intelligent fire map training system includes the following steps:

[0147] S1: After logging into the system, the management end adds, deletes, and modifies the training data in the networked data server and determines the training logic;

[0148] S2: The networked data server generates multiple independent map packages according to the training logic, and randomly selects map points in each map package and marks each map point;

[0149] S3: The trainer logs into the system through the training terminal to conduct training.

[0150] The step S3 includes the following steps:

[0151] S31: After logging into the system, a training interface is generated, and the trainer selects a training map according to the interface;

[0152] S32: After selection, the map is displayed on the training interface, and the trainer enters the location name of the marked point according to the marked point on the map.

[0153] In the step S32, the training personnel inputs using a full input method.

[0154] In the step S32, the logic of full input is:

[0155] B1: The training interface generates blank boxes corresponding to map markers;

[0156] B2: After the trainer clicks the blank box, he / she enters the marked address name in the blank box;

[0157] B3: The system uses a tolerance algorithm to verify the input name and the actual name of the map marker.

[0158] In step B3, the logic of the tolerance algorithm is:

[0159] B31: Set the tolerance ratio k;

[0160] B32: Get the total number of bytes p input by the trainer and the number of bytes q of the correct answer;

[0161] B33: Then compare and the size of k, where |p∩q| is the number of bytes that are the same in p and q;

[0162] B331: If It is determined that the information input by the trainer matches, and the result is "correct";

[0163] B332: If It is determined that the information input by the trainer does not match and the result is "error".

[0164] The networking method of the networked data server comprises the following steps:

[0165] C1: Classify trainers according to their training content and training skills;

[0166] C2: After the trainer logs into the system through his account, each training terminal is bound to the trainer;

[0167] C3: Classify the training terminals according to the classification results of the trainers to form multiple categories;

[0168] C4: Establish a communication encrypted LAN in each category, and then establish a decoding communication connection between the management terminal and each category.

[0169] Embodiment 7:

[0170] An intelligent fire map training system, comprising:

[0171] A management terminal, used to manage system content and training content;

[0172] Multiple training terminals for fire map training operations;

[0173] The networked data server has built-in map data and training logic content, and connects the management end and the training end through a networking algorithm, and has built-in data processing modules and data storage modules.

[0174] The working logic of the intelligent fire map training system includes the following steps:

[0175] S1: After logging into the system, the management end adds, deletes, and modifies the training data in the networked data server and determines the training logic;

[0176] S2: The networked data server generates multiple independent map packages according to the training logic, and randomly selects map points in each map package and marks each map point;

[0177] S3: The trainer logs into the system through the training terminal to conduct training.

[0178] The step S3 includes the following steps:

[0179] S31: After logging into the system, a training interface is generated, and the trainer selects a training map according to the interface;

[0180] S32: After selection, the map is displayed on the training interface, and the trainer enters the location name of the marked point according to the marked point on the map.

[0181] In the step S32, the training personnel inputs using a full input method.

[0182] In the step S32, the logic of full input is:

[0183] B1: The training interface generates blank boxes corresponding to map markers;

[0184] B2: After the trainer clicks the blank box, he / she enters the marked address name in the blank box;

[0185] B3: The system uses a tolerance algorithm to verify the input name and the actual name of the map marker.

[0186] In step B3, the logic of the tolerance algorithm is:

[0187] B31: Set the tolerance ratio k;

[0188] B32: Get the total number of bytes p input by the trainer and the number of bytes q of the correct answer;

[0189] B33: Then compare and the size of k, where |p∩q| is the number of bytes that are the same in p and q;

[0190] B331: If It is determined that the information input by the trainer matches, and the result is "correct";

[0191] B332: If It is determined that the information input by the trainer does not match and the result is "error".

[0192] The networking method of the networked data server comprises the following steps:

[0193] C1: Classify trainers according to their training content and training skills;

[0194] C2: After the trainer logs into the system through his account, each training terminal is bound to the trainer;

[0195] C3: Classify the training terminals according to the classification results of the trainers to form multiple categories;

[0196] C4: Establish a communication encrypted LAN in each category, and then establish a decoding communication connection between the management terminal and each category.

[0197] In the C4 step, the encryption method includes the following steps:

[0198] C41: Divide each sub-data table into multiple different sub-blocks, and number each sub-block sequentially;

[0199] C42: Encrypt different sub-blocks using different mathematical functions;

[0200] C43: The encrypted sub-blocks are then communicated using different threads.

[0201] In the C42 step, it specifically includes the following steps:

[0202] C421: Create a mapping function set f i a And the encryption function set f i b ;

[0203] C422: For the original data, firstly select the corresponding mapping function according to the sub-block number, and transform the data through mapping to obtain the result;

[0204] C423: Select the encryption function corresponding to the number in the encryption function according to the integer part of the result obtained;

[0205] C424: The result of the mapping function transformation is then transformed twice using an encryption function to obtain the ciphertext.

[0206] Embodiment 8:

[0207] An intelligent fire map training system, comprising:

[0208] A management terminal, used to manage system content and training content;

[0209] Multiple training terminals for fire map training operations;

[0210] The networked data server has built-in map data and training logic content, and connects the management end and the training end through a networking algorithm, and has built-in data processing modules and data storage modules.

[0211] The working logic of the intelligent fire map training system includes the following steps:

[0212] S1: After logging into the system, the management end adds, deletes, and modifies the training data in the networked data server and determines the training logic;

[0213] S2: The networked data server generates multiple independent map packages according to the training logic, and randomly selects map points in each map package and marks each map point;

[0214] S3: The trainer logs into the system through the training terminal to conduct training.

[0215] The step S3 includes the following steps:

[0216] S31: After logging into the system, a training interface is generated, and the trainer selects a training map according to the interface;

[0217] S32: After selection, the map is displayed on the training interface, and the trainer enters the location name of the marked point according to the marked point on the map.

[0218] In the step S32, the training personnel inputs using a full input method.

[0219] In the step S32, the logic of full input is:

[0220] B1: The training interface generates blank boxes corresponding to map markers;

[0221] B2: After the trainer clicks the blank box, he / she enters the marked address name in the blank box;

[0222] B3: The system uses a tolerance algorithm to verify the input name and the actual name of the map marker.

[0223] In step B3, the logic of the tolerance algorithm is:

[0224] B31: Set the tolerance ratio k;

[0225] B32: Get the total number of bytes p input by the trainer and the number of bytes q of the correct answer;

[0226] B33: Then compare and the size of k, where |p∩q| is the number of bytes that are the same in p and q;

[0227] B331: If It is determined that the information input by the trainer matches, and the result is "correct";

[0228] B332: If It is determined that the information input by the trainer does not match and the result is "error".

[0229] The networking method of the networked data server comprises the following steps:

[0230] C1: Classify trainers according to their training content and training skills;

[0231] C2: After the trainer logs into the system through his account, each training terminal is bound to the trainer;

[0232] C3: Classify the training terminals according to the classification results of the trainers to form multiple categories;

[0233] C4: Establish a communication encrypted LAN in each category, and then establish a decoding communication connection between the management terminal and each category.

[0234] In the C4 step, the encryption method includes the following steps:

[0235] C41: Divide each sub-data table into multiple different sub-blocks, and number each sub-block sequentially;

[0236] C42: Encrypt different sub-blocks using different mathematical functions;

[0237] C43: The encrypted sub-blocks are then communicated using different threads.

[0238] In the C42 step, it specifically includes the following steps:

[0239] C421: Create a mapping function set f i a And the encryption function set f i b ;

[0240] C422: For the original data, firstly select the corresponding mapping function according to the sub-block number, and transform the data through mapping to obtain the result;

[0241] C423: Select the encryption function corresponding to the number in the encryption function according to the integer part of the result obtained;

[0242] C424: The result of the mapping function transformation is then transformed twice using an encryption function to obtain the ciphertext.

[0243] The above description is only a preferred specific implementation manner of the present invention, but the protection scope of the present invention is not limited thereto. Any technician familiar with the technical field can make equivalent replacements or changes according to the technical scheme and inventive concept of the present invention within the technical scope disclosed by the present invention, which should be covered by the protection scope of the present invention.

Claims

1. An intelligent fire map training system, characterized in that: include: A management terminal, used to manage system content and training content; Multiple training terminals for fire map training operations; The networked data server has built-in map data and training logic content, and connects the management end and the training end through a networking algorithm, and has built-in data processing modules and data storage modules.

2. The intelligent fire map training system according to claim 1, characterized in that: The working logic of the intelligent fire map training system includes the following steps: S1: After logging into the system, the management end adds, deletes, and modifies the training data in the networked data server and determines the training logic; S2: The networked data server generates multiple independent map packages according to the training logic, and randomly selects map points in each map package and marks each map point; S3: The trainer logs into the system through the training terminal to conduct training.

3. The intelligent fire map training system according to claim 2 is characterized in that: The step S3 includes the following steps: S31: After logging into the system, a training interface is generated, and the trainer selects a training map according to the interface; S32: After selection, the map is displayed on the training interface, and the trainer enters the location name of the marked point according to the marked point on the map; In the step S32, the training personnel inputs using a selective input method or a full input method.

4. The intelligent fire map training system according to claim 3 is characterized in that: In the step S32, the logic of the selective input is: A1: The training interface generates blank boxes corresponding to map markers; A2: Set a drop-down arrow for each blank box; A3: After the trainer clicks the drop-down arrow, multiple options are displayed; A4: After the trainer selects one of the options, the system automatically selects the result and fills it into the blank box.

5. The intelligent fire map training system according to claim 3 is characterized in that: In the step S32, the logic of full input is: B1: The training interface generates blank boxes corresponding to map markers; B2: After the trainer clicks the blank box, he / she enters the marked address name in the blank box; B3: The system uses a tolerance algorithm to verify the input name and the actual name of the map marker.

6. The intelligent fire map training system according to claim 5, characterized in that: In step B3, the logic of the tolerance algorithm is: B31: Set the tolerance ratio k; B32: Get the total number of bytes p input by the trainer and the number of bytes q of the correct answer; B33: Then compare and the size of k, where |p∩q| is the number of bytes that are the same in p and q; B331: If It is determined that the information input by the trainer matches, and the result is "correct"; B332: If It is determined that the information input by the trainer does not match and the result is "error".

7. The intelligent fire map training system according to claim 1, characterized in that: The networking method of the networked data server comprises the following steps: C1: Classify trainers according to their training content and training skills; C2: After the trainer logs into the system through his account, each training terminal is bound to the trainer; C3: Classify the training terminals according to the classification results of the trainers to form multiple categories; C4: Establish a communication encrypted LAN in each category, and then establish a decoding communication connection between the management terminal and each category.

8. The intelligent fire map training system according to claim 7, characterized in that: In the C4 step, the encryption method includes the following steps: C41: Divide each sub-data table into multiple different sub-blocks, and number each sub-block sequentially; C42: Encrypt different sub-blocks using different mathematical functions; C43: The encrypted sub-blocks are then communicated using different threads.

9. The intelligent fire map training system according to claim 8, characterized in that: In the C42 step, it specifically includes the following steps: C421: Create a mapping function set f i a And the encryption function set f i b ; C422: For the original data, firstly select the corresponding mapping function according to the sub-block number, and transform the data through mapping to obtain the result; C423: Select the encryption function corresponding to the number in the encryption function according to the integer part of the result obtained; C424: The result of the mapping function transformation is then transformed twice using an encryption function to obtain the ciphertext.

10. The intelligent fire map training system according to claim 9, characterized in that: In the step C421, the mapping function is: where x min is the minimum value in the data, x max is the maximum value in the data; Where e is the base of natural logarithms; where x min is the minimum value in the data, x max is the maximum value in the data; f a (x) = x p , where p<1; in Any combination of .

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